|Year : 2021 | Volume
| Issue : 3 | Page : 282-288
Impact of Internet in school-going adolescents: a cross-sectional observational study
Shraddha Jadhav, Praveen Godara, Arun V Marwale, Gaurav P Murambikar, Deepanjali Deshmukh, Prince Garg
Department of Psychiatry, MGM Medical College and Hospital, N6, CIDCO, Aurangabad, Maharashtra, India
|Date of Submission||21-Jun-2021|
|Date of Acceptance||13-Aug-2021|
|Date of Web Publication||03-Sep-2021|
Dr. Praveen Godara
Department of Psychiatry, MGM Medical College and Hospital, N6, CIDCO, Aurangabad 431001, Maharashtra.
Source of Support: None, Conflict of Interest: None
Introduction: Internet addiction is an online-related, compulsive behavior that interferes with normal living and causes severe stress on family, friends, loved ones, and one’s work environment. The addiction behavior becomes unmanageable, completely dominates the addict’s life, and impacts relationships and work. Aim: To identify the level of Internet addiction among school-going adolescents and its associated factors. Materials and Methods: A descriptive, cross-sectional study was conducted among school-going adolescents of age 13–19 years in Aurangabad, Maharashtra. Stratified random sampling was adopted, and 602 students were enrolled. Individual interview and Internet addiction test (IAT), a self-report 20-item tool for adolescents and adults, were used. The content validity and reliability of the tool were established, and a pilot study was conducted. Results: Approximately 19.77% of students had full control of his or her usage; 67.11% of students experience frequent problems because of excessive Internet use, and 13.12% of students had significant problems because of Internet use. About 99.8% had used the Internet before, and 61.0% had their devices such as laptops (59.1%), tablets (26.1%), and cell phones (4.0%). In total, 59.5% use the Internet for entertainment and 10.3% for relieving loneliness. There was a significant association between IAT outcome and age group such that with an increase in age developed the risk of getting Internet addiction (P = 0.003). Conclusion: We observed that 13.12% had significant problems because of Internet use. The factors significantly associated with IAT outcome were age group, medium of education, a device to access the Internet, and whether parents know about student’s Internet activities.
Keywords: Adolescents, Internet addiction, online texting
|How to cite this article:|
Jadhav S, Godara P, Marwale AV, Murambikar GP, Deshmukh D, Garg P. Impact of Internet in school-going adolescents: a cross-sectional observational study. MGM J Med Sci 2021;8:282-8
|How to cite this URL:|
Jadhav S, Godara P, Marwale AV, Murambikar GP, Deshmukh D, Garg P. Impact of Internet in school-going adolescents: a cross-sectional observational study. MGM J Med Sci [serial online] 2021 [cited 2022 Jan 25];8:282-8. Available from: http://www.mgmjms.com/text.asp?2021/8/3/282/325544
| Key Messages:|| |
Internet addiction is increasing among adolescents school-going children. The increasing availability of smartphones and cheaper Internet services lead to more Internet addiction in the form of social media surfing and texting.
| Introduction|| |
Addiction is defined as a compulsive need for and use of a habit-forming substance characterized by tolerance and by well-defined physiological symptoms upon withdrawal, and broadly as persistent compulsive use of a substance known by the user to be harmful. Problematic Internet use (PIU) is also called compulsive Internet use or pathological computer use, or Internet addiction disorder (IAD). Such an addiction leads to compulsive behavior that interferes with normal living and causes severe stress on family, friends, loved ones, and one’s work environment. Internet addiction is also known as Internet dependency and Internet compulsivity. By any name, it is a compulsive behavior that completely dominates the person’s life and becomes the organizing principle of that person’s life. The Internet—like food or drugs in other addictions—provides the “high” and addicts become dependent on this cyberspace high to feel normal. They substitute unhealthy relationships for healthy ones. They opt for temporary pleasure rather than the deeper qualities of “normal” intimate relationships. Internet addiction follows the same progressive nature as other addictions. A person with Internet addiction struggles to control their behaviors and experiences despair over their constant failure to do so. Their loss of self-esteem grows, fueling the need to escape even further into their addictive behaviors. A sense of powerlessness pervades the lives of addicts. Studies suggest that one in eight Americans suffer from PIU. Those estimates are higher in China, Taiwan, and Korea where 30% or more of the population may experience PIU.
Internet addiction includes any online-related such as sexting (send [someone] sexually explicit photographs or messages via mobile phone and online sex addiction is still the most common form of Internet addiction); addiction to video games and online role-playing games are the fastest growing forms of Internet addiction, especially in China, Taiwan, and Korea studied by Jang et al. Men are more likely to become addicted to online games, cyberporn, and online gambling, whereas women are more likely to become addicted to sexting, texting, social media, eBay, and online shopping as reported by Anderson. National surveys in India revealed that over 70% of people with Internet addiction also suffered from other addictions, mainly to drugs, alcohol, smoking, and sex. Relationship problems were found in almost 75% of the cases, and addicts use interactive online applications such as social media, virtual communities, video games, or online gaming as a safe way of establishing new relationships and more confidently relating to others through the virtual world.
Adolescents are exceptionally vulnerable and receptive during this period and can become drawn to the Internet as a form of release. Over time, this can lead to an addiction. They are especially attracted to new technological methods of communication, which offer interaction with others and at the same time provide anonymity, the impression of belonging to a community, and a sense of social acceptability. With this background in mind, we conducted a study to find out Internet addiction in Indian adolescents. The objectives of the study were: (a) to assess the level of Internet addiction among students from secondary school and (b) to assess the association between sociodemographic variables and Internet addiction.
| Materials and methods|| |
A descriptive, cross-sectional study was carried out among school-going adolescents of age 13–19 years from Aurangabad city, Maharashtra from October 2014 to December 2016.
Sample size and sampling strategy
The prevalence of Internet addiction was identified as 6% in India, and the sample size was calculated to be 542 using the formula
However, we decided to enroll 602 students considering 20% error. Study participants were selected using a stratified random sampling method. Secondary schools in Aurangabad city were divided into three categories: (a) Marathi and semi-English schools, (b) English medium schools, and (c) other medium schools (Urdu, Telugu, and Hindi). Two schools from each category were randomly chosen. A total of six schools were selected, and all the male and female students of age 13–19 years who have used or are using the Internet were included in the study. Consent from the school authority and the participant’s parents was taken. The approval for the study was obtained from the Institutional Ethical Committee and Research Recognition Committee of the university.
A semi-structured pro forma was used to collect information on demographic profiles, habits associated with Internet use.
A standardized Internet addiction test (IAT) by Dr. Kimberly Young was used. It comprises 20 items rated on a five-point Likert scale (from 1 = not at all, to 5 = always), and it measures the extent of individual’s problems due to the Internet use in daily routine, social life, productivity, sleeping patterns, and feelings. Based on the total score obtained on the test, the individual is placed into one of three categories: average online user (from 20 to 39) who has full control of his or her usage; experiences frequent problems because of excessive Internet use (from 40 to 69); or has significant problems because of Internet use (from 70 to 100).
The content validity of the tool was established by requesting experts to validate the tool and give their valuable suggestions. Few questions as suggested by experts were added to structured pro forma, for the study to be feasible in local settings. The reliability of the edited tool was established by using the split-half method. The reliability for pro forma and IAT by Dr. Kimberly Young test was estimated to be 0.783 and 0.862, respectively.
Students of age group between 13 and 19 years of both genders who have used or are using the Internet are included; those who were not willing to participate in the study, students not meeting the age criteria, and students meeting the age criteria but finished secondary high school were excluded.
The Internet addiction was assessed among 60 school adolescents by individual interviews using both study tools (10 from each school mentioned above). The study pro forma was modified according to the results and discussion with experts. The study was found to be feasible and was followed by the final study. Each participant was explained in detail the purpose and method of the study. The informed written consent was obtained from the principal of the school and parents of participating students. Then the individual interview was conducted with precaution to maintain privacy.
The data were analyzed using Statistical Software for Social Sciences v 20. Descriptive statistical analysis was carried out using frequency and percentages. Inferential statistical analysis used the Chi-square test to show the association of various risk factors with IAT scores.
| Results|| |
A total of 602 adolescents from all six schools participated. The mean age of the students was found to be 14.56 ± 0.79 years. Demographic details of the participants are presented in [Table 1]. Our study shows 30.2% had a device to access the Internet (61.0% had their device), whereas 69.8% did not have one. A vast majority (99.8%) had used the Internet previously. Among those who owned a device, 59.1% had a laptop, 26.1% a tablet, 10.8% a desktop (personal computer), and 4% cell phone. More than half of the students (58.6%) spent more than 2h on the Internet. A higher proportion of students (58.1%) preferred Internet café to use the Internet, whereas only 11.6% would use the Internet at home. However, 45.2% of students answered that most of the time, their parents knew about their Internet activities.
It was found that 42% of the students have used the Internet at an age of 15 years or less and 58% of students have used the Internet when they were older than 15 years of age. The majority of the students (34.7%) preferred surfing general websites and chatting online (20.6%). More than half of the students (59.5%) preferred using the Internet for entertainment, 25.9% use the Internet for homework/research, and the others use the Internet as a mode to relieve loneliness or any other reasons [Figure 1]. More than half of the students (67.11%) experience frequent problems because of excessive Internet use according to the IAT score [Table 2]. Among the sociodemographic variables, age and medium of education were found to be significantly associated with IAT outcome (P < 0.05). There is a steep increase in the number of 15-year-old students who were in risk and addicted categories. A greater proportion of Marathi and semi-English mediums were found to be at risk for Internet addiction [Table 3]. Internet use-related variables such as a device to access, whether own or not, and parents’ knowledge about student’s Internet activity were found to be significantly associated with IAT outcome (P < 0.05) [Table 4].
|Table 2: Distribution of students according to IAT by Dr. Kimberly Young|
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|Table 4: Association between IAT outcome and Internet use–related variables|
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| Discussion|| |
Several studies have been conducted across the world, especially among adolescents concerning Internet addiction. This study is a preliminary step toward understanding the extent of Internet addiction among school-going students in India. In the present study, 67.11% of students experience frequent problems because of excessive Internet use according to the IAT score and 13.12% have significant problems because of Internet use as per the IAT score.
A study conducted in Jaipur city in India concluded that Internet addiction was present among 28.57% of high school students. The prevalence of Internet addiction in their study was in line with studies reported by other authors but was more compared with our study. The use of different diagnostic scales for Internet addiction, different population characteristics, presence of comorbidities, and failure to demarcate recreational use from essential use of the net are responsible for varying prevalence of Internet addiction in different studies.
The use of the Internet between social networking and other purpose was found to be statistically significant for Internet addiction in this study. Social networking comprises 84% of the web audience in India and takes up 21% of all time spent online. Research across countries and continents has suggested that social networking and online chatting are among the highest-ranked online activities and are associated with Internet addiction. The need for socialization as evidenced by social enhancement in extroverts and social compensation in introverts may be a reason behind the teeming use of social networking sites.
Also, loneliness, social anxiety, and shyness are positive correlates of Internet addiction that may drive an individual to such means of communication online owing to the comfort of anonymity, nullification of the need for nonverbal communication, and ease of approach. Probably for the fact that the majority of students accessed the net via home and were thus under parental constraints and financial limitations, cybersex, gambling, and shopping were not found significant in this work, which is in dissonance with other studies.
A study on Internet addiction among adolescents revealed 50% increased odds for males to be addicted to the Internet (odds ratio = 1.5, 95% confidence interval = 1.1–2.2) when compared with females. In a Finnish study, men had a significantly higher mean score on the IAT than did women. Available data from the community and online surveys, as well as clinical samples, suggest that Internet addiction appears to have a male preponderance and suggested that males are more likely to use the Internet to fuel other addictions such as gambling and gaming. But in our study, this difference was not significant.
It has been observed that out of 404 students who are at risk of developing Internet addiction, 31.4% of students were females and 68.6% of students were males. And out of 79 Internet addicted students, 35.5% of students were females and 64.5% of students were males. In our study, a larger number of the study participants were boys, which may be due to the sex ratio in the classroom that showed a higher male preponderance.
In another study from Mangalore, the prevalence of Internet addiction (representing moderate and severe addiction) was 18.88% among undergraduate medical students. A study on IAD among medical students in China reported a prevalence of 16.2%.
The prevalence of Internet addiction in Iranian students was 51.3% mild, 5.4% moderate, and 0.9% severe, whereas 42.4% of students were not addicted to the Internet. These results were inconsistent with our study as more than half of the students (67.11%) experience frequent problems because of excessive Internet use according to the IAT score. Another study from India evaluated Internet addiction by using Davis Online Cognition Scale in school-going adolescents aged 16–18 years. They reported a prevalence of 18%, which is comparable with our study as 13.12% of students had significant problems because of Internet use. The reasons for huge variation in the prevalence rates could be due to difficulty in conceptualizing Internet addiction, heterogeneity of population studied, lack of availability of standard diagnostic criteria, studies failing to differentiate between essential and nonessential Internet use, and nonconsideration of psychiatric comorbidity in some of the studies.,,
The study reveals that there was no correlation between the working status of both parents and Internet use. Parental job status and unavailability can have an impact on boredom and loneliness with few parental restrictions leading to increased Internet use. Our study showed that more than 60% of adolescents had either their mobile phones or laptops or both indicative of a growing trend of adolescents being given early access to gadgets at home. This is higher compared with a study in adolescents in Hong Kong in December 2009 that reported a prevalence of 8% in 699 Internet users aged 16–24 years. Our study reports a higher prevalence than that of 0.7% reported from college students in a study done in 2013. This may also indicate growing trends for Internet addiction, and other sociodemographic parameters may also play a role.
During the study, it has been noticed that 10.3% of students used the Internet to relieve loneliness, whereas 59.5% of students used the Internet for entertainment purposes. Most subjects reported Internet use for social networking as well as entertainment, which was in line with a study done in Croatia where adolescents mostly used the Internet for entertainment (905/1078, 84.00%). Students often download music and movies from the Internet. In India, girls may experience more restrictions in extending friendships in real life because of societal and moral norms and thus may resort to social media.
One of the limitations of the study is that we did not consider the design effect in the calculation of sample size, and others being recall and social desirability bias that may have affected the outcome. However, we filled the void of many previous studies by avoiding sampling bias. We did not recruit participants through e-mail, group networks, and postings on websites designed for the Internet or other addicts, thereby limiting itself to a self-selected sample of participants who have some interest or psychological investment in the topic and would have been more likely to participate, thus leading to a biased sample.
| Conclusion|| |
In our study, we found out that 13.12% of students had significant problems because of Internet use. There was a significant association between IAT outcome and age group. It was seen that as the age increases so does the level of addiction, and 15-year-old students were the most affected. Age and medium of education, Internet use-related variables such as a device to access, whether own or not, and parents’ knowledge about student’s Internet activity were found to be significantly associated with IAT outcome.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
Institutional Ethics Committee for Research on Human Subjects has given their approval vide their letter no. MGM-ECRHS/2014 dated December 5, 2014 for undertaking the proposed study.
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[Table 1], [Table 2], [Table 3], [Table 4]